Explorations in the Economics of Choice and Chance

选择和机会经济学的探索

• 批准号: 1949329
• 负责人: Lones Smith
• 金额: $ 28.2万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1949329&HistoricalAwards=false
• 关键词: Explorations; Economics; Choice; Chance

This award funds research in economic theory. The researcher plans four distinct projects. The first models an individual who is searching across possible options one-by-one. The goal is to understand the best way to search when the individual already knows that there is a specified number of options and has some information about options. This project will help us understand the value of providing information to people before they search through structured search lists. Applications include optimal design of web searches and optimal design of job/ hiring searches. The second project builds and analyzes a model of medical testing, to determine optimal testing protocols when definitive clinical tests are more expensive than less informative alternatives. The third project will develop a modified model of contagions that accounts for evasive human behavior that increasingly slows the contagion as it grows more prevalent. The model could contribute to more accurate epidemiological forecasting. The final project will look at demand for risky investments, and in particular investments that are similar to rollover lotteries. The goal is to better understand why these investments are rapidly growing and how best to design them. This project contains four methodologically related sub-projects on the economics of choice and chance. The first research project will develop a sequential model of search in environments with finitely many options and prior knowledge of the options. This is an essential innovation on search theory, since rarely does one search in the stereotypical informational vacuum. This project rather explores search that transpires in smartly ordered lists, as offered in web search contexts. Recall optimally occurs, with older options more often recalled. Early work suggests an answer to a long open question: one expects to search longer when the prize distribution is more disperse. The second project will enrich a standard epidemiological model with a random pairwise matching population game where individuals choose how vigilantly to avoid acquiring it. The unique Nash equilibrium will yield a behavioral twist on the SIR Model. We will estimate this parametric model with data from the 2009 H1N1 influenza pandemic, and show that allowing for human ingenuity facing an ongoing contagion improves the explanation of the data. The third project will explore how should one proceed with costly but informative medical tests before acting. Our main qualitative conjecture, motivated by numerical simulations, will determine when one transitions from low cost to high cost medical testing, depending on the testing precision or medical urgency. The main conjecture of the project upends an insight from a well-known 2001 paper on the optimal level of experimentation that assumed continuous time. The final project will explore an implicit market cleared by probabilities. This proposes a simple economic explanation for lottery gambling that is consistent with the larger set of facts revealed by rollover lotteries: People gamble because they derive utility both from the money gains (varying across people), and the gambling experience. The results are applicable to a range of investments with risky payoffs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项资助经济理论研究。研究人员计划了四个不同的项目。第一个模型是一个正在逐个搜索可能选项的个人。我们的目标是了解当个人已经知道有指定数量的选项并且有一些关于选项的信息时，搜索的最佳方式。这个项目将帮助我们理解在人们通过结构化搜索列表进行搜索之前向他们提供信息的价值。应用程序包括网络搜索的优化设计和工作/招聘搜索的优化设计。第二个项目建立和分析了一个医学测试模型，以确定最佳的测试协议时，确定性的临床测试比信息量较少的替代品更昂贵。第三个项目将开发一个改进的传染模型，该模型考虑到人类的逃避行为，随着传染变得越来越普遍，这种行为会越来越慢。该模型有助于更准确的流行病学预测。最后一个项目将研究对风险投资的需求，特别是类似于滚动彩票的投资。我们的目标是更好地理解为什么这些投资迅速增长，以及如何最好地设计它们。该项目包括四个方法论上相关的选择和机会经济学的子项目。第一个研究项目将开发一个顺序模型的搜索环境中的许多选项和先验知识的选项。这是搜索理论的一个重要创新，因为很少有人在刻板的信息真空中进行搜索。这个项目更倾向于探索在网络搜索环境中提供的智能有序列表中出现的搜索。回忆是最佳的，旧的选项更经常被回忆。早期的研究为一个长期悬而未决的问题提供了答案：当奖金分配更分散时，人们希望搜索更长的时间。第二个项目将丰富一个标准的流行病模型与随机配对匹配的人口游戏，其中个人选择如何警惕，以避免获得它。独特的纳什均衡将产生一个行为扭曲的SIR模型。我们将用2009年H1N1流感大流行的数据来估计这个参数模型，并表明考虑到人类面对持续传染的聪明才智，可以改善对数据的解释。第三个项目将探讨在采取行动之前应该如何进行昂贵但信息丰富的医学测试。我们的主要定性猜想，由数值模拟的动机，将决定何时从低成本过渡到高成本的医疗测试，这取决于测试精度或医疗紧急性。该项目的主要猜想颠覆了2001年一篇著名论文中关于假设连续时间的最佳实验水平的见解。期末专题将探讨一个以机率出清的隐含市场。这为彩票赌博提出了一个简单的经济学解释，与滚动彩票揭示的更大的事实集一致：人们赌博是因为他们从金钱收益（因人而异）和赌博体验中获得效用。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。